A key resource of most, if not all enterprises is knowledge. For example, in a customer service environment, customers expect prompt and correct answers to their information requests. These information requests may relate to problems with products the customer has purchased, or to questions about products they may decide to purchase in the future. In most cases, the answer to the customer's question exists somewhere within the enterprise. In other cases, the answer may have existed in the enterprise at one time, but is no longer there. The challenge is to find the best answer and provide it to the customer in a timely manner.
Typical approaches to providing support information to customers on the Internet, either provide a static structure (predefined hyperlinks) for customers to navigate to the information they need, or they provide simple “lookup” facilities for finding documents or products, such as database searches or full-text searches for keywords appearing in documents or in product descriptions. These types of approaches are typically not tailored to the customer (no personalization) and do not typically engage the customer in a multiple step interaction (no conversational dialog), wherein the information is elicited from the customer.
Other current approaches for providing support information to customers, such as case-based reasoning systems and expert systems, provide a multiple step interaction with customers, but they require the business to set up very complex “case” structures or expert-system rule sets that define the problems and their resolutions in great detail. These approaches are often brittle and it is typically very costly for the business to add new rules and cases to these systems.
Still other Web-based systems check for particular textual content without the advantage of context or domain knowledge. Consequently, they generally do not reliably and consistently return the desired information. This is at least partly due to the fact that language is not only inherently ambiguous, but also because it is susceptible to expressing a single concept any number of ways using numerous and unrelated words and/or phrases. By simply searching for specific key words, prior art search engines fail to identify other alternatives that may also be helpful.
Consequently, there is a strong need in the art for an improved method and apparatus for retrieving relevant information from large knowledge bases. There is also a need for providing this capability to relatively unsophisticated users.